Amazon SageMaker Now Supports Apache MXNet 1.3 and TensorFlow 1.11
Amazon SageMaker now supports Apache MXNet 1.3 and TensorFlow 1.11 in its built-in containers for MXNet and TensorFlow respectively. This makes it easier to run MXNet and TensorFlow scripts, while taking advantage of the capabilities Amazon SageMaker offers, including a library of high-performance algorithms, managed and distributed training with automatic model tuning, one-click deployment, and managed hosting.
Amazon SageMaker now supports Apache MXNet 1.3 and TensorFlow 1.11 in its built-in containers for MXNet and TensorFlow respectively. This makes it easier to run MXNet and TensorFlow scripts, while taking advantage of the capabilities Amazon SageMaker offers, including a library of high-performance algorithms, managed and distributed training with automatic model tuning, one-click deployment, and managed hosting.
Apache MXNet 1.3 comes with Gluon package enhancements, ONNX export, and TensorRT integration among many other enhancements. The Gluon package enhancements enable dynamic networks based on Gluon RNN layers to be hybrid, exported, and used in the inference APIs. TensorRT integration results in increased throughput and reduced latency. With Apache MXNet 1.3, the script format for training with the built-in MXNet containers in SageMaker is similar to using MXNet outside SageMaker, enabling enables seamless movement of workloads between SageMaker and your infrastructure. TensorFlow 1.11 comes with C, C++, and Python functions for querying kernels.
The Amazon SageMaker built-in containers for MXNet with version 1.3 and TensorFlow with version 1.11 are now available in all regions where Amazon SageMaker is available. See the documentation for additional information.